Developing a dynamic equilibrium system in Escherichia coli to improve the production of recombinant proteins

大肠杆菌 重组DNA 生产过剩 生物 寄主(生物学) 自溶(生物学) 膜蛋白 蛋白质生物合成 计算生物学 基因 生物化学 遗传学
作者
Zixu Zhang,Yuzhou Wang,Fang-Tong Nong,Yan Xu,Chao Ye,Yang Gu,Xiaoman Sun,He Huang
出处
期刊:Applied Microbiology and Biotechnology [Springer Nature]
卷期号:106 (18): 6125-6137 被引量:4
标识
DOI:10.1007/s00253-022-12145-0
摘要

The combination of Escherichia coli BL21 (DE3) and the pET expression system is used extensively for the expression of various recombinant proteins (RPs). However, RP overexpression often introduces a growth burden for the host, especially in the case of toxic proteins. The key to solving this problem is to reduce the host burden associated with protein overproduction, which is often achieved by regulating the expression or activity of T7 RNAP or growth-decoupled systems. However, these strategies mainly relieve or interrupt the robbing of host resources, and do not eliminate other types of host burdens in the production process. In this study, we constructed a production system based on a dynamic equilibrium to precisely relieve the host burden and increase the RP production. The system is composed of three modules, including the overexpression of basic growth-related genes (rRNA, RNAP core enzyme, sigma factors), prediction and overexpression of key proteins using the enzyme-constrained model ec_iECBD_1354, and dynamic regulation of growth-related and key protein expression intensity based on a burden-driven promoter. Using this system, the production of many high-burden proteins, including autolysis protein and E. coli membrane proteins, was increased to varying degrees. Among them, the cytosine transporter protein (CodB) was most significantly improved, with a 4.02-fold higher production compared to the wild strain. This system can effectively reduce the optimizing costs, and is suitable for developing various types of RP expression hosts rapidly. KEY POINTS: • The basic growth-related resources can relieve the host burden from recombinant protein. • The enzyme-constrained model can accurately predict key genes to improve yield. • The expression intensity can be dynamically adjusted with changes in burden.
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